DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. HugeGraph vs. LeanXcale vs. Sadas Engine

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. HugeGraph vs. LeanXcale vs. Sadas Engine

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Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

A fast-speed and highly-scalable Graph DBMS

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Relational DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

github.com/hugegraph
hugegraph.apache.org

www.leanxcale.com

www.sadasengine.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

hugegraph.apache.org/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Baidu

LeanXcale

SADAS s.r.l.

Initial release

2016

2018

2015

2006

Current release

0.9

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

AIX
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
Java
Perl
Python
R

Groovy
Java
Python

C
Java
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

depending on used storage backend, e.g. Cassandra and HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Access rights for users, groups and roles according to SQL-standard

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